A forecast of ophthalmology practice trends in Saudi Arabia: A survey of junior residents
Bibliographic record
Abstract
PURPOSE: The aim of this study is to identify the trends in practice pattern among current ophthalmology residents in Saudi Arabia. MATERIALS AND METHODS: Ophthalmology residents in Saudi Arabia responded anonymously to a written survey between November 2007 and February 2008. The survey contained questions on demographic information, medical education, residency training, career goals and factors influencing their career choice. The data were categorized by gender. The influence of gender on outcome was assessed in a univariate fashion using the Chi-square or Fisher exact test when appropriate. A P-value of 0.05 or less was considered statistically significant for all analyses. RESULTS: A total of 68 out of 85 residents (80%) responded to the survey. Over one-half of the residents preferred to pursue a fellowship within Saudi Arabia (53%), while others (25%) planned to train in North America. The majority of respondents wished to practice in an urban setting (63%). Anterior segment was the most desired subspecialty, while general ophthalmology and glaucoma were not a popular choice. Most residents were interested in refractive surgery (77%) and research (75%). The main factor influencing the decision to pursue ophthalmology was the ability to combine medicine and surgery (97%), while a positive elective experience was also an important factor, particularly for female respondents (91% vs. 57%; P < 0.001). CONCLUSION: Concerted efforts are required to encourage adoption to ophthalmic practice in public institutions rather than in private practice. In addition training in underrepresented subspecilaties should be encouraged to ensure adequate ophthalmic care for all citizens of Saudi Arabia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".